With the advancement in technology, there has been increasing interest in collecting data from flying vehicles. Examples of flying vehicles include but is not limited to airplane, helicopter, unmanned aerial vehicle, satellite, balloon (hereinafter jointly referred to as UAV). Flying vehicles offer significant advantage over ground based sensing of mobility by providing an ability to be deployed remotely and to quickly and easily cover large areas. This capability allows acquiring remote intelligence from a safe standoff distance and offers a unique data collection tool. Data can be obtained for different real life events from these flying vehicles. For example, data can be collected to monitor physical properties of a power line network, measure forest growth, and measure construction of houses, analyze moving objects, initialize weapons and the like. Data can be spatial (geometrical) information of real world objects present in geographical area and can be collected by arrangement of sensors in flying vehicles. Collected data can include positioning data, observation data and the like. Positioning data includes but is not limited to WGS-84 (GPS coordinates) including altitude or relative position and pose to one or more objects or to one or more other UAV's. On the other hand, observation data includes but is not limited to information collected by cameras (2D, 3D, infrared, high definition, high frequency and the like), and measurements from temperature sensor, Lidar, audio sensor and X-rays.
A typical system for the above stated requirement includes a UAV to collect positioning and observation data and storage medium (SSD, flash memory, CD-ROM, hard disk and the like) to store the collected data. However, in the traditional system, the data needs to be transmitted physically for analysis, as no communication device is capable of handling the large amount of data frequently on the order of tens of terabytes. Moreover, the speed of data collected by multiple sensor devices in flying vehicles is not compatible with the current communication systems. In addition, the present systems do not allow error correction in the measured data during the collection of the observations. Further, the systems do not allow real time analysis of data and thus only provide static analyses after the fact. This eliminates the possibility of making quick analysis to enable a reaction analysis results in real time.
In addition, due to multiple steps required in long processing cycle, manual intervention for handling and analysis of data is required. However, manual intervention may result in quality risks, long delays in processing, and other similar problems.